The present disclosure relates to evaluation and training of cognitive computing systems, and more specifically, to techniques and mechanisms for improving the results generated by a knowledge canvassing system.
Generally, a graph, knowledge graph, or graph network, can be utilized to represent facts. A graph database, also known as a semantic information network or a network database, includes a (usually sparsely, but multiply connected) directed graph with information stored at named nodes and information relating nodes stored at named directed edges. Knowledge canvassing consists of a user input of information, disambiguation of the input information to known information stored in the knowledge graph, and the return of selected result information drawn from the relationships stored in the knowledge graph. In some systems, text passages that provide evidence of the identified relationships may also be returned. Knowledge canvassing systems are often designed to return the most interesting and/or meaningful information related to the input information to provide a response to a user's general interest in the query information.